TY - GEN
T1 - Neighborhood preserving Nonnegative Matrix Factorization for spectral mixture analysis
AU - Mei, Shaohui
AU - He, Mingyi
AU - Shen, Zhiming
AU - Belkacem, Baassou
PY - 2013
Y1 - 2013
N2 - Nonnegative Matrix Factorization (NMF) has been successfully employed to address the mixed-pixel problem of hyperspectral remote sensing images. However, minimizing the representation error by NMF is not sufficient for SMA since the unmixing results of NMF are not unique. Therefore, in this paper, a neighborhood preserving regularization, which preserves the local structure of the hyperspectral data on a low-dimensional manifold, is proposed to constrain NMF for unique solution in SMA. As a result, a Neighborhood Preserving constrained NMF (NP-NMF) algorithm is proposed for SMA of highly mixed hyperspectral data. Finally, experimental results on AVIRIS data demonstrate the effectiveness of our proposed NP-NMF algorithm for SMA applications.
AB - Nonnegative Matrix Factorization (NMF) has been successfully employed to address the mixed-pixel problem of hyperspectral remote sensing images. However, minimizing the representation error by NMF is not sufficient for SMA since the unmixing results of NMF are not unique. Therefore, in this paper, a neighborhood preserving regularization, which preserves the local structure of the hyperspectral data on a low-dimensional manifold, is proposed to constrain NMF for unique solution in SMA. As a result, a Neighborhood Preserving constrained NMF (NP-NMF) algorithm is proposed for SMA of highly mixed hyperspectral data. Finally, experimental results on AVIRIS data demonstrate the effectiveness of our proposed NP-NMF algorithm for SMA applications.
KW - hyperspectral images
KW - Nonnegative Matrix Factorization
KW - Spectral Mixture Analysis
UR - http://www.scopus.com/inward/record.url?scp=84894238367&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2013.6723348
DO - 10.1109/IGARSS.2013.6723348
M3 - 会议稿件
AN - SCOPUS:84894238367
SN - 9781479911141
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2573
EP - 2576
BT - 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
T2 - 2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Y2 - 21 July 2013 through 26 July 2013
ER -